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terms.csv

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-TERM,CONTEXT
-aes() mapping,Maps variables to visual properties like x y color size in ggplot
-alpha (significance level),Probability threshold for Type I error commonly set at 0.05
-alternative hypothesis,Research hypothesis claiming an effect or difference exists
-animal welfare protocols,Ethical guidelines ensuring humane treatment in research with vertebrates
-ANOVA (one-way),Tests for mean differences across three or more groups
-assumptions of linear regression,Linearity normality of residuals and homoscedasticity requirements
-augment(),broom function that adds residuals fitted values and diagnostics to model data
-bar plot,Shows counts or means for categorical variables
-bcPower(),Function in car package for Box-Cox power transformations
-binary data,Categorical variable with two levels like yes/no or presence/absence
-bioinformatics and computational biology methods,Sequence alignment phylogenetics protein folding machine learning for genomic data
-biological replicate,Independent experimental units providing true replication
-blinding,Concealing treatment assignment to reduce bias
-blocking,Grouping by known variable like age or location to control its effects
-Bonferroni correction,Adjusts alpha by dividing by number of tests to control Type I error
-bootstrapping,Resampling with replacement to estimate confidence intervals and standard errors
-Box-Cox transformation,Power transformation to normalize data and stabilize variance using optimal lambda
-boxplot,Displays median IQR whiskers and outliers for group comparisons
-broom package,Tidies model output into data frames for easier manipulation
-case-control study,Compares groups with and without outcome to identify risk factors
-categorical data,Qualitative groups like species or treatment levels
-Central Limit Theorem,Sample means approach normal distribution as n increases regardless of population shape
-central tendency,Measures of data center including mean median and mode
-chi-squared goodness of fit,Tests if observed frequencies match expected frequencies for one categorical variable
-chi-squared test of independence,Tests if two categorical variables are associated or independent
-CO2 dataset,Built-in R dataset with plant uptake measurements used for regression examples
-coefficient of determination (R²),Proportion of variance in response explained by predictors
-Cohen's d,Standardized effect size measure for mean differences
-confidence interval (95%),Range likely to contain true parameter value with 95% confidence
-confounding variable,Factor that correlates with both treatment and outcome
-conservation biology methods,Population viability analysis habitat modeling biodiversity assessment species monitoring
-continuous data,Quantitative measurements like weight length or concentration
-control group,Baseline comparison receiving no treatment or standard treatment in experiments
-Cook's distance,Measures influence of each observation on regression model identifies outliers
-cor.test(),R function for testing correlation significance between two variables
-correlation coefficient (r),Standardized measure of linear association from -1 to 1
-cross-over design,Each participant receives all treatments in different periods with washout between
-cross-sectional study,Data collected at single time point across different subjects
-data transformation,Mathematical modifications like log or square root to meet assumptions
-discrete data,Count data taking only integer values
-double-blind,Neither participants nor researchers know treatment assignment
-dplyr,R package for data manipulation with verbs like select filter mutate
-ecology and evolution methods,Mark-recapture species distribution modeling community ecology population genetics
-effect size,Magnitude of difference between groups independent of sample size
-ethics in research,Principles ensuring participant welfare and scientific integrity
-experimental unit,Smallest independent unit receiving treatment assignment
-exploratory data analysis (EDA),Initial data examination to understand patterns before formal testing
-facet_grid,Creates grid of plots by two categorical variables in ggplot2
-facet_wrap,Creates small multiples by single variable for quick comparisons
-factorial design,Tests multiple factors and their interactions simultaneously
-false discovery rate,Expected proportion of false positives among rejected hypotheses
-field study,Research in natural environment with ecological validity
-filter(),dplyr function to subset rows based on conditions
-fitted values,Model predictions for each observation in regression
-Fligner-Killeen test,Non-parametric test for equal variances across groups
-generalized linear model (GLM),Extension of linear models for non-normal response distributions
-genomics and molecular methods,CRISPR gene editing RNA-seq ChIP-seq proteomics single-cell analysis
-geom_bar,Bar chart layer for categorical data in ggplot2
-geom_boxplot,Boxplot layer for group comparisons in ggplot2
-geom_histogram,Histogram layer for distribution visualization
-geom_point,Scatterplot layer for continuous relationships
-geom_smooth,Adds regression line or smoothed curve to plots
-ggplot2,R package for creating layered graphics using grammar of graphics
-group_by(),dplyr function to perform operations by groups
-heteroscedasticity,Unequal variance violating assumptions of parametric tests
-histogram,Shows distribution of continuous variable using bins
-homoscedasticity,Equal variance assumption for groups or across predictor range
-hypothesis testing framework,Structured approach to testing claims using null and alternative hypotheses
-IACUC,Institutional Animal Care and Use Committee overseeing vertebrate research ethics
-in vitro,Experiments in controlled environment outside living organism
-in vivo,Experiments conducted in living organisms
-informed consent,Ethical requirement for human subjects to voluntarily agree to participate
-Institutional Review Board (IRB),Committee ensuring ethical standards in human subjects research
-intercept,Predicted y value when x equals zero in regression equation
-interquartile range (IQR),Range between 25th and 75th percentiles robust to outliers
-iris dataset,Classic R dataset with 150 flower measurements for classification examples
-Kolmogorov-Smirnov test,Tests if sample comes from specified distribution like normal
-kurtosis,Measure of distribution tail heaviness relative to normal
-lambda (λ),Transformation parameter in Box-Cox determining optimal power
-leverage,Measure of how extreme predictor values are potential for influence
-linear regression,Models relationship between predictor and continuous response variable
-lm(),R function for fitting linear models returns coefficients and diagnostics
-log transformation,Common transformation for right-skewed data or multiplicative relationships
-longitudinal study,Data collected from same subjects over multiple time points
-marine and environmental science methods,Ocean sampling environmental DNA water quality assessment climate modeling
-MASS package,R package containing functions for modern applied statistics
-mean,Average value sum divided by n central tendency measure used in t-tests ANOVA
-median,Middle value when ordered robust central tendency measure for boxplots IQR
-microbiology and immunology methods,Flow cytometry ELISA viral quantification microbiome analysis antibiotic resistance testing
-mode,Most frequent value in dataset third measure of central tendency
-model diagnostics,Checking assumptions through residual plots QQ plots and formal tests
-multiple comparisons problem,Increased Type I error risk when conducting multiple tests
-multiple regression,Linear model with two or more predictor variables
-mutate(),dplyr function to create or modify columns
-negative control,Treatment known to have no effect checks for artifacts
-neuroscience methods,Electrophysiology fMRI optogenetics behavior tracking connectomics analysis
-normality,Bell-shaped Gaussian distribution assumption for parametric tests checked Week 3
-null hypothesis,Statement of no effect or no difference to be tested
-observational study,No treatment manipulation only observation of existing variation
-observer bias,Researcher expectations influence data collection or interpretation
-one-sample t-test,Tests if sample mean differs from hypothesized population value
-open science,Transparency practices including data sharing preprints reproducible code
-ordinary least squares (OLS),Method minimizing sum of squared residuals to fit regression line
-outlier,Data point substantially different from other observations
-p-value,Probability of obtaining results as extreme as observed if null hypothesis true
-paired t-test,Compares matched observations like before-after measurements
-Palmer Penguins dataset,Modern alternative to iris with 344 penguin measurements
-parametric tests,Statistical tests assuming specific probability distributions
-pilot study,Small preliminary study testing feasibility and methods
-pipe operator (|> or %>%),Chains functions together for readable workflows in R
-plant biology methods,Photosynthesis measurement growth assays metabolomics gene expression tissue culture
-plot(),Base R function for creating diagnostic plots from lm objects
-positive control,Treatment known to produce effect validates experiment
-post-hoc tests,Pairwise comparisons following significant omnibus test like ANOVA
-power (1-β),Probability of correctly rejecting false null hypothesis
-power analysis,Calculates needed sample size given expected effect alpha and power
-powerTransform(),car package function to find optimal Box-Cox lambda value
-pre-registration,Publishing study design and analysis plan before data collection
-predictor variable,Independent variable used to predict outcome in regression
-protected health information (PHI),Confidential patient data requiring special ethical handling
-pseudoreplication,Incorrectly treating non-independent observations as replicates
-QQ plot,Graphical method comparing data distribution to theoretical normal
-quasi-experimental design,Lacks random assignment but seeks causal inference
-R programming language,Statistical computing environment widely used in biological research
-R squared,Proportion of variance explained by regression model
-random sampling,Selection where each member has equal probability of inclusion
-randomization,Random assignment to treatments prevents systematic bias
-randomized controlled trial (RCT),Gold standard experimental design with random treatment assignment
-range,Maximum minus minimum quick variability check sensitive to outliers
-regression assumptions,Requirements including linearity normality and constant variance
-regression diagnostics,Tools for checking model assumptions using residuals and influence measures
-repeated measures design,Same subjects measured under multiple conditions reduces variance
-replication,Multiple independent observations per treatment group essential Week 9 concept
-research misconduct,Fabrication falsification plagiarism violations of scientific integrity
-residual standard error,Estimate of standard deviation of residuals around regression line
-residuals,Differences between observed and predicted values in regression
-response variable,Dependent variable being predicted in regression analysis
-sample size (n),Number of independent observations affects power and uncertainty
-sampling distribution,Distribution of sample statistics across repeated sampling
-scatterplot,Plots two continuous variables to show relationships
-select(),dplyr function to choose specific columns from data frame
-Shapiro-Wilk test,Statistical test for normality effective for small to moderate samples
-simple linear regression,Model with single predictor and continuous response
-skewness,Asymmetry in distribution with longer tail on one side
-slope,Rate of change in y per unit change in x regression coefficient
-sqrt transformation,Square root transformation for count data or moderate skew
-standard deviation,Average spread of data points around the mean
-standard error,Standard deviation of sampling distribution measures precision
-statistical methods in biomedicine,Clinical trials survival analysis epidemiology biomarkers meta-analysis
-statistical significance,Result unlikely due to chance alone typically p < 0.05
-stratification,Dividing population into subgroups before sampling
-sum of squares,Total squared deviations used in ANOVA and regression calculations
-summarize(),dplyr function to calculate summary statistics
-summary(),R function displaying model coefficients tests and fit statistics
-systems biology methods,Network analysis metabolic modeling multi-omics integration pathway analysis
-t-statistic,Test statistic for t-tests ratio of effect to standard error
-technical replicate,Multiple measurements of same unit not true replication
-three Rs principle,Replacement reduction refinement in animal research ethics
-tidy(),broom function converting model output to tidy data frame
-tidyverse,Collection of R packages for data science including ggplot2 and dplyr
-transformation parameter,Value like lambda determining type and strength of transformation
-Tukey HSD,Post-hoc test for pairwise comparisons after significant ANOVA
-two-sample t-test (unpaired),Compares means of two independent groups
-Type I error,False positive rejecting true null hypothesis
-Type II error,False negative failing to reject false null hypothesis
-variance,Square of standard deviation measuring data dispersion
-violin plot,Combines boxplot with kernel density to show distribution shape
-Welch's t-test,Modified t-test for unequal variances between groups
-Winsorization,Replacing extreme values with less extreme ones to reduce outlier impact